I have a pandas dataframe df with the following features: visitor_id, feature_1, feature_2, ..., feature_100, truth_labels

I implemented the following model on sklearn:

1st step: scaling df.drop(['visitor_id', 'truth_labels'], axis=1) using sklearn.preprocessing.StandardScaler()

2nd step: clustering df.drop(['visitor_id', 'truth_labels'], axis=1) using sklearn.cluster.MiniBatchKMeans() in 10 clusters. Set df['cluster'] to corresponding clusters.

3rd step: fit 10 sklearn.linear_model.LogisticRegression() on df.drop(['visitor_id'], axis=1), one per cluster.

I have two questions:

1- Is it possible to build a Pipeline in order to aggregate these three steps? In particular, how can I specify that I want to train 10 distinct sklearn.linear_model.LogisticRegression() models on my data splitted by clusters?

2- Is it possible to save this full pipeline? How?

  1. Yes.
  2. Yes.

1) You can implement your own logic for pipeline step. You can find detailed example in sklearn documentation.

In your case it would be:

from sklearn.linear_model import LogisticRegression
from sklearn.base import BaseEstimator, TransformerMixin
from sklearn.pipeline import Pipeline, make_pipeline

class TenLogisticRegressionsClassifier(BaseEstimator, TransformerMixin):

    def __init__(self, N=10):
        self.estimators = { i:LogisticRegression() for i in range(N)  }

    def fit(self, X, y=None):
        for k,v in self.estimators.items():
            # Here some logic to divide dataset
            v.fit(newX, newY)

    def predict(self, X, y=None):
        for k,v in self.estimators.items():
            # Here some logic to divide dataset

pipeline = Pipeline([('something',   TenLogisticRegressionsClassifier())])
# or
pipeline = make_pipeline(TenLogisticRegressionsClassifier())

2) Answer is on Stack Overflow

from sklearn.externals import joblib
joblib.dump(pipeline, 'pipeline.pkl')
# or, if you want 1 file:
joblib.dump(pipeline, 'filename.pkl', compress = 1)

Then you can load it and use:

pipeline_loaded = joblib.load('filename.pkl')
  • 1
    $\begingroup$ Could you add a brief summary of the SO link? Sometimes SO questions are closed (or deleted by their original questioner) so there is still a chance of linkrot, and it would be nice to have a self-contained answer. $\endgroup$ – Silverfish Apr 26 '16 at 12:10

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